CoralCare+ is an AI-powered predictive maintenance software that enables real-time monitoring of machines and equipment, allowing potential failure signs to be detected before they occur.
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By analyzing data collected through sensors using artificial intelligence and data analytics methods, it monitors the health of machines and equipment and provides feedback before failures arise.
Properties
Artificial intelligence learns the normal operating characteristics of a machine, detects even the smallest deviations, and evaluates potential failures.
AI analyzes sensor data and past failure records to predict when equipment components might fail, optimizing maintenance processes.
AI uncovers complex relationships behind failures, identifies root causes, and helps businesses prevent recurring issues.
Workflow
Workflow Information
Sensor data from machines is collected through NoSFC Terminals and transmitted to the CoralReef IoT platform. Operating parameters such as temperature, vibration, and pressure are stored in a centralized data pool.
Collected data is cleaned, missing information is completed through preprocessing, and then prepared for analysis. Machine performance trends and potential anomalies are identified.
Processed data is analyzed using machine learning algorithms to examine machine operating patterns. Model optimization ensures the development of the most accurate prediction models.
Trained AI models are integrated into the CoralReef MES system, enabling predictive maintenance and anomaly detection. This allows for early failure prediction, optimizing maintenance processes and preventing production disruptions.
Benefits
Reporting
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